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1808.08531
Cited By
DeepTracker: Visualizing the Training Process of Convolutional Neural Networks
26 August 2018
Dongyu Liu
Weiwei Cui
Kai Jin
Yuxiao Guo
Huamin Qu
HAI
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Papers citing
"DeepTracker: Visualizing the Training Process of Convolutional Neural Networks"
17 / 17 papers shown
VIOLET: Visual Analytics for Explainable Quantum Neural Networks
Shaolun Ruan
Zhiding Liang
Qian-Guo Guan
Paul Griffin
Xiaolin Wen
Yanna Lin
Yong Wang
194
1
0
23 Dec 2023
A Comparative Visual Analytics Framework for Evaluating Evolutionary Processes in Multi-objective Optimization
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Ya-Wen Huang
Zherui Zhang
Ao Jiao
Yuxin Ma
Ran Cheng
184
9
0
10 Aug 2023
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
Angelos Chatzimparmpas
R. Martins
I. Jusufi
K. Kucher
Fabrice Rossi
A. Kerren
FAtt
237
183
0
22 Dec 2022
Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022
Bum Jun Kim
Hyeyeon Choi
Hyeonah Jang
Dong Gu Lee
Wonseok Jeong
Sang Woo Kim
175
7
0
15 May 2022
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series
Dongyu Liu
Sarah Alnegheimish
Alexandra Zytek
K. Veeramachaneni
AI4TS
164
27
0
10 Dec 2021
Interactive Analysis of CNN Robustness
Stefan Sietzen
Mathias Lechner
Judy Borowski
Ramin Hasani
Manuela Waldner
AAML
148
15
0
14 Oct 2021
T3-Vis: a visual analytic framework for Training and fine-Tuning Transformers in NLP
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Raymond Li
Wen Xiao
Lanjun Wang
Hyeju Jang
Giuseppe Carenini
ViT
161
24
0
31 Aug 2021
Towards data-driven filters in Paraview
Journal of Flow Visualization and Image Processing (JFVIP), 2021
Drishti Maharjan
Peter Zaspel
94
0
0
11 Aug 2021
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles
G. Cantareira
R. Mello
F. Paulovich
AAML
159
10
0
18 Mar 2021
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020
Zhihua Jin
Yong Wang
Qianwen Wang
Yao Ming
Tengfei Ma
Huamin Qu
HAI
507
43
0
22 Nov 2020
InstanceFlow: Visualizing the Evolution of Classifier Confusion on the Instance Level
Michael Pühringer
A. Hinterreiter
M. Streit
165
19
0
22 Jul 2020
HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020
Qianwen Wang
W. Alexander
J. Pegg
Huamin Qu
Min Chen
VLM
124
13
0
12 Feb 2020
ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion
IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), 2019
A. Hinterreiter
Peter Ruch
Holger Stitz
Martin Ennemoser
J. Bernard
Hendrik Strobelt
M. Streit
150
51
0
02 Oct 2019
SANVis: Visual Analytics for Understanding Self-Attention Networks
Visual .. (VISUAL), 2019
Cheonbok Park
Inyoup Na
Yongjang Jo
Sungbok Shin
J. Yoo
Bum Chul Kwon
Jian Zhao
Hyungjong Noh
Yeonsoo Lee
Jaegul Choo
HAI
182
41
0
13 Sep 2019
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
International Conference on Human Factors in Computing Systems (CHI), 2019
Qianwen Wang
Yao Ming
Zhihua Jin
Qiaomu Shen
Dongyu Liu
Micah J. Smith
K. Veeramachaneni
Huamin Qu
HAI
184
109
0
13 Feb 2019
Analyzing the Noise Robustness of Deep Neural Networks
Mengchen Liu
Shixia Liu
Hang Su
Kelei Cao
Jun Zhu
AAML
130
9
0
09 Oct 2018
RuleMatrix: Visualizing and Understanding Classifiers with Rules
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2018
Yao Ming
Huamin Qu
E. Bertini
FAtt
168
238
0
17 Jul 2018
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